The model is based on the k-nearest neighbor (KNN) algorithm and uses facial parameters such as symmetry and proportions to determine attractiveness.
The researchers used datasets, including the World’s 100 Most Beautiful Female Faces 2020 videos and the Lab London Database, which includes the faces of men and women ages 18 to 54.
Artificial intelligence was trained on these datasets, and then the technology showed extraordinary accuracy in judging the attractiveness of faces, comparable to human assessments.
It is reported that the accuracy of the new approach is significantly higher than previous studies and the correlation coefficient exceeds the estimates of the individuals.
According to experts, this study is important for psychology, neuroscience and computer science. It provides a new perspective on the concept of facial attractiveness and its quantification using machine learning.
Source: Ferra
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